Content uploaded by Robert N Fitzgerald
Author content
All content in this area was uploaded by Robert N Fitzgerald on Jan 10, 2014
Content may be subject to copyright.
300
W Chapter 13
Collaborative Research Tools: Using Wikis
and Team Learning Systems to Collectively
Create New Knowledge
Robert Fitzgerald and John Findlay
Introduction`
In the fi rst decade of the twenty-fi rst century, technological and social change is accelerat-
ing faster than ever before. Seemingly isolated and “under control” local or regional issues
are now being transmitted throughout global economic, technological, and management
systems in minutes and days rather than months and years. The global fi nancial crisis is one
recent example of this. Major differences between the experts (scientists and other research-
ers) about issues such as global warming, the use of nanotechnology or nuclear power often
polarize the key debates producing confl ict and little action. Decision theory has taught
us that expertise is highly domain specifi c and therefore differences in opinion and strat-
egy are understandable and to be expected. However, the real problem arises when experts
move from their descriptive expertise to the normative activity of making predictions as to
what constitutes ideal or optimal social practice. Many years ago, Rittel and Webber (1973)
made the important distinction between wicked and tame problems. Tame problems are
those that can be solved by the technical applications of expertise and knowledge. Wicked
problems as those that are contentious and controversial with no clear solution—they are
social problems such as welfare or poverty, requiring a social dialogue between experts and
nonexperts. Wicked problems are not solved by information alone. In his 1980s best-selling
book about the paradigm shift from the Industrial Age to the Information Age, futurist John
Naisbitt noted, “We are drowning in information but starved for knowledge” (1982, p. 17).
Three decades later, it could be argued that we are now drowning in knowledge, but starved
of its wise application to the wicked problems that face us.
Solving Wicked Problems Through Democratized Research
There is a pressing need for processes of social research and some aspects of the natu-
ral sciences to become more democratized, so that nonexperts can not only participate
13_HesseBiber_Chap13.indd 30013_HesseBiber_Chap13.indd 300 9/14/2010 9:44:00 PM9/14/2010 9:44:00 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 301
directly in the process of knowledge creation, but also in its immediate implementation.
In fi elds such as knowledge management or business innovation, there is already a shift
away from the traditional model of expert-neophyte to communities of knowers. Here,
citizens play an active role as content creators, self-managing their community teams
to participate more or less equally in the production and consumption of knowledge.
The citizen journalism movement is one such example, where local citizens armed with
mobile phones and other devices report on the news as it happens. The initial reaction
of the traditional news media was to ignore or ridicule this movement as ill informed
and amateurish, but now every major news service encourages their viewers to share and
contribute their stories. The power of this form of journalism is unquestionable—who
can forget the YouTube video of Neda Agha-Soltan’s death during the protests in Iran
in June 2009. Within a short space of time, this video became a symbol of the Iranian
protests and the widespread condemnation of the Iranian government’s handling of the
protests. As this example shows, central to increasing community participation has been
the role played by new information and communication technologies, in particular Web
2.0 applications designed around what has been termed an “architecture of participation”
(O’Reilly, 2004). However, most Web 2.0 tools are designed to achieve a technical require-
ment of participation, rather than higher forms of contribution implicit in learning and
knowledge creation. Mayfi eld (2006) describes the power law of participation according
to how people use different online tools. At the high end of the scale, which he calls collab-
orative intelligence, tools support the joint production of knowledge in which the object
of inquiry is transformed with the active interaction of the participants through a process
of synthesis. At the other end of the participation spectrum, which Mayfi eld characterizes
as collective intelligence, participants engage in reproducing, comprehending, and clas-
sifying existing knowledge (Figure 13.1).
Mayfi eld’s model offers a tantalizing account of the potential of participation to
engage users in higher forms of activity or collaborative intelligence. Within the debate
about the impact of Web 2.0 developments, some commentators allude to the potential
for the many to create knowledge (Surowiecki, 2004) and the increased opportunities
Power law of participation
Collective
intelligence
Collaborative
intelligence Lead
Moderate
Collaborate
Refactor
Write
Network
Share
Subscribe
Comment
Ta g
Favourite
Read
Low threshold High engagement
Figure 13.1
13_HesseBiber_Chap13.indd 30113_HesseBiber_Chap13.indd 301 9/14/2010 9:44:00 PM9/14/2010 9:44:00 PM
302 The Handbook of Emergent Technologies in Social Research
for social production of knowledge (Benkler, 2006), while others lament the loss of
expertise and rigor (Keen, 2007) in this new environment. Researchers such as Hasan
and Crawford (2006, p. 10) offer a more nuanced perspective and see people and tech-
nology as engaged in a complex socio-technological system of “self-directed knowl-
edge work where people, engaged in a collective activity, are allowed and enabled to
choose the technical components as needed to automate operations, leaving them with
more time to deal with the knowledge components of their actions.” In these socio-
technical systems, there are shifts to new forms of joint production and new ways of
knowing become possible. In the academic fi eld, there is also a shift away from research
conducted purely via the scientifi c method to a more inclusive connected approach to
knowledge creation (Palmer, 1998).
Research as a Specialized Form of Learning
We begin this chapter with the proposition that good research is a specialized form of
learning that engages participants in mutual inquiry and a dialectical or knowledge build-
ing discourse. In this chapter, we consider the potential of two emergent technologies,
wikis and team learning systems, that both embody an architecture of participation that
engages users in the coproduction of new knowledge via a process of research. In academe,
research and learning are inextricably entwined in a form of ongoing research-education
exchange, which is also dialectical, and is transformed as it is transferred or used (Shariq,
1999). As new theories are formulated and the new knowledge is applied, gaps develop in
the theory that point to inconsistencies that evolve into new unanswered questions that
become the subject of further research.
Although the scientifi c method has been extraordinarily successful, educational insti-
tutions have become the custodians of a curious form of inert knowledge (Palmer, 1998),
presided over by “high priests” of both the knowledge and the methods for acquiring
knowledge, access to which only a few are allowed. Academic institutions are designed to
objectively discover new knowledge and acculturate chosen neophytes into their method
of creating new knowledge. Further down the line in the school education system, the
problem is critically apparent. Teachers, who often have little or no formal role in either
the creation of new knowledge or the development of pedagogy, receive accreditation
from the universities in both the practice of teaching and the fi eld in which they specialize,
such as mathematics, science, or the arts. The knowledge they pass on to their students is
an inert, theoretical form that may bear little or no relationship to the practical kinds of
knowledge or skills students will require to be successful in the workplace. The objective
expert is often removed from the source of identifi ed errors in a theory by several layers
of obfuscation. The expert’s role is to interpret what they know for “amateurs” who “are
full of bias” (Palmer, 1998, p. 100) and to select some to be indoctrinated into the world of
objective knowing. Experts are trained in methods designed to prevent their subjectivity
from intruding on the interpretation of the object so it remains in its “pristine” form, but
this ensures that most participants in the learning process remain disengaged from the
learning process (Palmer, 1998) (Figure 13.2).
Palmer proposes a “connected knowing” model in which all participants in the
research-learning process are in touch as both observers of and interactors with the
13_HesseBiber_Chap13.indd 30213_HesseBiber_Chap13.indd 302 9/14/2010 9:44:00 PM9/14/2010 9:44:00 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 303
subject. He argues that this close relationship with the subject results in a more truth-
ful and faithful type of learning that is more real and credible for the amateur than the
remote, abstract scientifi c models that emerge from objective research. People arrive at
truth via “an eternal conversation about things that matter, conducted with passion and
discipline” (p. 104). Palmer’s model affords the amateur a new status not as nonexpert but
rather closer to the Latin meaning of the word “amateur” as a passionate and enthusiastic
pursuer of an objective within a community of knowers (Figure 13.3).
This approach, which combines both research and teaching functions, allows the ama-
teur to participate in the knowledge-creation process alongside experts. During the inter-
action, the amateur learns through a process of immersion and imitation in the manner
fi rst identifi ed by Vygotsky (1978) as collective play. Vygotsky showed that people learn in
three main ways:
1. with support through the zone of proximal development, which has been
described as the zone between what a learner can do independently and
what they can do with guidance (as exemplifi ed by the present “objective”
education-research system);
2. through a process of inner speech or dialogue while engaging with an external
tool, where a new skill is fi rst practiced externally, then internalized;
3. through play with others with what begins as a process of imitation of the
activity of others. Three mediating factors—tools, signs, and other people—are
present in play so that people are able, via cooperation, to “raise the demand
on themselves and with that bring themselves into the zone of proximal
development” (Brostrom, 1999, pp. 250–251) and thereby master ideas they
cannot achieve in nonplay settings.
In order to deal with growing size and complexity, many business organizations and
some government agencies have found it necessary to decentralize their knowledge
Figure 13.2
Amateur Amateur
Expert
Object
Amateur Amateur Amateur
13_HesseBiber_Chap13.indd 30313_HesseBiber_Chap13.indd 303 9/14/2010 9:44:00 PM9/14/2010 9:44:00 PM
304 The Handbook of Emergent Technologies in Social Research
building and decision-making capabilities to the stakeholders. Accelerating change on
many scales has made it diffi cult for centrally controlled organizations to function
as successfully as they were able to in slower times. Sluggish behemoths of organiza-
tions tend to be displaced in a Darwinian competition by faster moving and more
fl exible organizations, capable of either rapidly implementing knowledge newly cre-
ated by others or directly creating their own knowledge—to improve their products,
processes, and decision-making methods. In a world in which accelerating change has
become a critical factor, organizations can no longer plan rationally as their primary
strategy. In order to deal with a multiplicity of scenarios, a playful approach to learn-
ing has emerged in the form of search conferences, brainstorming sessions to generate
and link ideas that better fi t the context, scenario planning, simulations, and case stud-
ies, in which groups work together in order to determine what might happen in the
real-world. Leadbeater (2008) points to this new approach of playful joint-knowledge
construction in his online book, “We think: Why mass creativity is the next best thing.”
He says:
The power of mass creativity is about what the rise of the likes of Wikipedia and YouTube,
Linux and Craigslist means for the way we organise ourselves, not just in digital businesses
but also in schools and hospitals, cities and mainstream corporations. My argument is that
these new forms of mass, creative collaboration announce the arrival of a society in which
participation will be the key organising idea rather than consumption and work. People
want to be players not just spectators, part of the action, not on the sidelines. (p. 1)
Knower
Knower
SubjectKnower Knower
KnowerKnower
Knower Knower
Figure 13.3
13_HesseBiber_Chap13.indd 30413_HesseBiber_Chap13.indd 304 9/14/2010 9:44:01 PM9/14/2010 9:44:01 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 305
The emergent tools that most closely fi t this new kind of world of playful co-creation, and
which have applications in the world of research, are wikis and the Zing team learning
system, both of which show potential to enable sharing, exchange, and joint production.
Emergent Research Tools: Wikis and the Zing Team Learning System
Wikis and the Zing team learning system (TLS) have separate origins and different appli-
cations. Wikis build on the metaphor of a page, while team learning systems draw on the
metaphor of a conversation. The two notions are highly complementary, as will become
clear in the following sections.
A wiki is a Web page that can be easily edited by a group of users. This somewhat
simplistic description belies the collaborative power that can arise when groups of people
need to work on a document together. In 1995, Ward Cunningham developed the fi rst
wiki as a system for Web publication. He wanted a system that was accessible, simple to
use, and reliable and that would enable nontechnical users to publish material on the
Internet. Core to his original specifi cation was the principal that any author would auto-
matically be an editor as well. In their early days, wiki systems used a specifi c editing
language; however, with their widespread use has come the preference for more useable
WYSIWYG (What You See Is What You Get) editors. Fitzgerald (2007) has argued that
the combined author/editor role built-in to wikis supports a model of collaboration and
knowledge building that is more consistent with constructivist approaches to learning
(Vygotsky, 1978) and the development of communities of practice (Wenger, McDermott,
& Snyder, 2002). Each wiki page comprises four different views of the document: Article,
Discussion, Edit, and History.
The Article tab represents the current version of the document, while the Discussion
tab is a place where comments and discussions are recorded about the development of the
document. The Edit section allows the user to modify the page, while the History tab pro-
vides a complete revision history of the document and has the facility to compare versions
and/or revert pages to a previous version. This rich descriptive environment documents
both the process and the product.
Wikis have a role to play at different stages of the research process. At the start
of research work, they are not only a richly connected way to access both the his-
tory of the development of knowledge in a fi eld, along with the messy contradictions
and competing ideas, but also a place that fl ags the latest ideas and provides links to
connected ideas—akin to a giant Wittgensteinian language game. For the researcher,
Wikipedia-style sites are becoming the fi rst port of call to obtain a broad overview of
the state of the art and locate immediate links to journal articles and other references,
sometimes even the original source documents from the researchers who initiated the
fi eld. Although wikis may not necessarily be as exhaustive as a library, both physical
in the forms of documents and artifacts, and virtual, as is now available online, a wiki
helps to organize information and research articles around themes and related themes
so that what people regard as the most vital or interesting is brought forward for the
community’s attention. Wikis also allow data and other artifacts to be shared with
other researchers and they can be very useful at the stage when joint authors are spark-
ing off each other’s ideas. Wikis are generally readily accessible with several service
13_HesseBiber_Chap13.indd 30513_HesseBiber_Chap13.indd 305 9/14/2010 9:44:01 PM9/14/2010 9:44:01 PM
306 The Handbook of Emergent Technologies in Social Research
providers such as www.wikispaces.com and pbwiki.com, allowing users to establish a
public wiki at no charge, with private and customizable wikis available from $US5 to
$US50 per month.
There is no question that over recent years, Wikipedia has become a popular
and valued source of information that enables collaborative interaction among users
(LeLoup & Ponerio, 2006; Lih, 2004). The potential of wikis to engage users has
been documented in the area of e-government (Wagner, Cheung, & Ip, 2006) and
in what has become known as participatory journalism (Lih, 2004). A key feature of
wikis makes them well suited to the rapid development and sense-making required
in research. Wikis promote a short edit-review cycle within a highly visible (and
often public) environment where the complete history of the page edits is easily
accessible.
The result is that knowledge can be quickly developed and authenticated by the com-
munity of users (Lih, 2004), supporting both member checking and more elaborate com-
munity authentication. Social media researchers Bruns and Bahnisch (2009) identify the
features that make wikis exemplary forms of social media including:
1. their relatively low threshold of participation—the system is accessible to a wide
range of users;
2. highly granular participation tasks—a variety of tasks can be undertaken from
simple editing through to major conceptual organization;
3. an assumption of user equipotentiality—users are able to actively participate in
the system irrespective of their skill or experience;
4. shared ownership of content—a collaborative model of knowledge creation is
promoted where the community owns the content.
In addition to the research benefi ts that arise from the use of wiki systems, perhaps one
of the most compelling comes from researchers’ need to demonstrate that their research
process is open for comment and critique. Too often, research constructs participants as
sources of data who only have a role to play during that data collection phase. Research
plans and processes are usually predetermined and often closed to comment and critique.
According to writers such as Jenkins (2006) and Bruns (2008), we live in a highly partici-
patory world of blogs and wikis where users want to share their opinion and cocreate.
Researchers that set themselves as the experts and do not engage participants as cocreators
may well fi nd it increasingly diffi cult to recruit participants and are ultimately at risk of
producing low-quality research fi ndings.
Zing Team Learning System
The Zing team learning system is a tool that brings together into a single platform four
aspects of human interaction: decision and learning processes, communicating and relat-
ing processes, facilitation and leadership methods, and mechanisms for recording and
sharing ideas. Taken together, these four aspects allow the neophyte or amateur to per-
form many of the roles of an expert consultant or teacher and help people create new
knowledge together. The tool guides participants—researchers, learners, or decision
13_HesseBiber_Chap13.indd 30613_HesseBiber_Chap13.indd 306 9/14/2010 9:44:01 PM9/14/2010 9:44:01 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 307
makers—through a series of open-ended discussable questions to arrive at a conclu-
sion, decision, action plan, new model, or theory. Each session is led by a facilitator who
employs a facilitation model or “etiquette” to organize or orchestrate the group activity so
that all the participants engage in the same activity at the same time. The most frequently
used “etiquette” is known as the Talk-Type-Read-Review cycle, which involves discussing
the topic for several minutes, typing the ideas, reading the ideas aloud, and looking for
patterns in the ideas, which is a sense-making step. Other etiquettes can also be used to
organize the group process. Participants using a team learning system are presented with
a series of rich questions that guide their discussion. The participants discuss a question
and then type their ideas, which are presented on the screen. Participants are able to not
only see their own ideas as they are generated, but also all other ideas as they form. The
data is coded so that the concept is recorded together with the identity of the contributor
(Figure 13.4).
In a team learning session, all the participants “talk” at the same time, which gives
everyone at the meeting an opportunity to have an equal say, whereas in a conventional
business meeting the order of discussion is determined by a chairperson or by taking
turns, and in the classroom, the order is often determined by the teacher. Another advan-
tage of the tool is the ease with which neophyte facilitators can quickly master the role of
facilitator (Findlay & Newman, 2005).
The ability to view all the ideas as they are created ensures that participants recall or
make connections to related ideas, which promotes assimilation, orchestration, and inte-
gration. As the narrative is revealed and shaped, the developing ideas become triggers or
scaffolds for further and usually richer and more integrated ideas.
Figure 13.4
13_HesseBiber_Chap13.indd 30713_HesseBiber_Chap13.indd 307 9/14/2010 9:44:01 PM9/14/2010 9:44:01 PM
308 The Handbook of Emergent Technologies in Social Research
In the research fi eld, team learning systems have been used for data collection (Waters
& Callan, 2003; Findlay, 2009; Whymark, Callan, & Purnell, 2004), activity theory research
(Findlay, 2009; Lee & Crawford, 2002), ethical dilemma analysis (Findlay & Newman,
2005), social research (Fitzgerald & Findlay, 2004; Caldwell, 2006), focus groups (Ward
& Hawkins, 2003; Moyle & Fitzgerald, 2008), and Q methodology (Hasan & Crawford,
2006; Meloche & Hasan, 2008). The following fi ve examples illustrate the range of possible
research applications of the Zing team learning system.
Example 1: Focus Group Research
Whereas most focus group research seeks to perpetuate the expert knower-amateur rela-
tionships and to minimize the interactions between the participants, the team learning
tool facilitates a dynamic type of conversation that evolves and allows the researcher to
ask “abductive,” “what if” type questions that project the discussion beyond the current
paradigm.
Caldwell (Caldwell, 2006; Caldwell, Bhowon, Daby, & Harris, 2009), an education con-
sultant and former Dean of Education at Melbourne University, has conducted numerous
focus groups using the team learning system with head teachers and principals in Africa,
Australasia, Asia, Europe, and South America. The workshops have had a dual purpose: to
collect data about issues facing educators around the world as they seek to adapt to accel-
erating societal change, and to plan how to implement the changes. Participants share
their knowledge and perspectives about the future directions of school education and
arrive at new conclusions via a guided “vibrant and exhilarating” conversation. Typical
of a guided discussion process is the following sequence of questions asked of teachers,
principals, and administrators in Maritius in 2007, where Caldwell tags each question so it
relates to an integrated theoretical model the participants are asked to consider and use:
1. What differences would a visitor observe if your school is offering a world-class
quality education in 2012 (vision)?
2. What new knowledge and skills are needed by teachers at your school if this
vision is to be realized (intellectual capital)?
3. In what ways can individuals, organizations, and institutions, not currently
involved, assist your school in its efforts to offer a world-class quality education
(social capital)?
4. What changes in values, beliefs, and attitudes are needed in your school and
its community if the school is to succeed in its efforts to deliver a world-class
quality education (spiritual capital)?
5. What changes in planning and budgeting processes in your school will help
ensure that scarce resources are well-targeted (fi nancial capital)?
6. What changes will be required in the roles of school leaders (leadership and
governance)?
Findlay (2009), Dodd (private communication, 2007), and Phillips (2009) have sepa-
rately used the tool to conduct “student voice” focus groups to collect data from students
about their school or classroom experiences, as inputs to programs to help school princi-
pals and teachers understand how their students are responding to different pedagogical
13_HesseBiber_Chap13.indd 30813_HesseBiber_Chap13.indd 308 9/14/2010 9:44:02 PM9/14/2010 9:44:02 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 309
approaches. Students were asked what they like or do not like about both school and their
lessons, and which pedagogical approaches they prefer or least like. Findlay, Fitzgerald, and
Hobby (2004) reported on a series of focus groups conducted with teachers and students in
the United Kingdom. They showed that senior students were more socialized into the school
system and did not expect changes from schools, whereas junior secondary students still
hoped for improvements that would improve their learning experiences. The Zing system
enabled the researchers to work with the students to create a narrative about their experience
of school. Asked about their patterns of computer use at school and home and what changes
they would prefer to the way they learned and school was organized, the senior students said
“there is little or no opportunity to use these tools” in school and spent very little time using
computers at school “because they are shoddy” and there are “too many restrictions.” They
wanted schools to be more fl exible, involve “more interaction” and greater use of technology,
and allow students to “take more control over their learning” and “have their own opinions”
and enjoy “better teacher techniques” for “different types of learners.”
Example 2: Action Research
Newman and Findlay (2008) employed an action research approach to concurrently
develop a new software program known as “Working Wisely” on the team learning system
platform and undertake research into the use of professional discourse by early childhood
professionals. The development task was to translate a complex paper-based generic pro-
cess for resolving ethical dilemmas into a series of 10 guided discovery workshops. The
research task was to use the feedback from the participants to inform the design process
and to develop an understanding of how rich, dialectical, and dialogical discourse models
married to ethical discourse can bring about personal change and a change in their rela-
tions with the children and families they served. A set of workshops was devised in which
participants were presented with a series of ethical dilemmas. At each stage of the process,
the participants were asked to consider how they would deal with each new complication,
and at the end of the workshop to then develop their own theoretical models and rubrics.
During the course of the research project, there was a shift from informal everyday lan-
guage by the participants in the project, which is summarized by one person who reported
she now “felt more like a professional than a child-minder.”
Example 3: Nominal Group Technique
The nominal group technique (NGT) is a rapid decision-making method that obtains
multiple inputs from group members on a particular problem or issue and then applies
a structured group technique for prioritizing those inputs (Delbecq & van de Ven, 1971).
Willcox and Zuber-Skerrit (2003) report on the use of the tool for action research using
NGT. In this process, participants are asked to contribute their responses to a broad
research question in several rounds of idea generation. Then, without criticism or com-
ment so they are open to be infl uenced by all the ideas, participants choose a small number
of ideas they regard as the most important, place them in rank order, and consolidate the
votes. The technique is regarded as nominal because the groups act individually within
a group context. Wilcox and Zuber-Skerrit compared the tool with a fl ip-chart process
13_HesseBiber_Chap13.indd 30913_HesseBiber_Chap13.indd 309 9/14/2010 9:44:02 PM9/14/2010 9:44:02 PM
310 The Handbook of Emergent Technologies in Social Research
and showed the tool compressed the research cycle from 2 hr to 30 min, reduced research
fatigue and provided a “fun” experience.
Example 4: Q Methodology
The Q methodology is a systematic research procedure used to study people’s opinions or
attitudes. Participants are presented with a set of statements about a topic and asked to
rank order in a process referred to as Q sorting. The team learning system speeds up the
collection of statements for the Q methodology research, whether from face-to-face or
online participants. The tool then allows them to rank the statements in order of impor-
tance, which can be used as input for Q method analysis software. Hasan and Crawford
(2006) reported on the use of the online version of the team learning system to remotely
collect statements for a Q methodology research activity from geographically dispersed
participants. Hasan, Meloche, Pfaff, and Willis (2007) employed a face-to-face version
of the team learning system to survey subjective attitudes toward the use, adoption, and
acceptance of a corporate wiki and explain the lack of use. In both examples, the factors
that emerged refl ected the priority views of the participants. Meloche and Hasan (2008, p.
3) said that the use of the team learning system “is particularly effective in the Concourse
stage of Q Methodological research where the participants can freely engage in conversa-
tions and the material is freely typed and projected for all to see. The process engages the
participants and promotes discussion. The researcher is also provided with a digital copy
of the discussion and no additional or obvious effort is required of the participants.”
Example 5: Voting and Surveys
The team learning system allows poll or survey data to be collected simultaneously from
multiple users. The participants contribute their responses in real time. The contributions
and the aggregated results are in full view of all the participants. Voting tools include
Yes–No for a simple poll, an X–Y tool to chart two factors (e.g., risk analysis, where the
probability of an event is assigned one number and the impact a second number), a rank-
order tool, a weight tool, and a scale-voting tool. The team learning tool allows the facilita-
tor to prepare a variety of surveys using response scales that vary from 3 to 7 items.
The voting system also allows researchers to conduct instant polls during the course of
a research activity to collect self-report data about the state of individual members of the
group or the group as a whole. Findlay (2009) used the tool to collect data about the level
of engagement of work groups and classroom learners before, during, and after a workshop
activity in order to determine the impact on the interaction by different kinds of teach-
ing styles. Findlay applied the concept of Flow to study high-level engagement. The Flow
experience, which has been widely studied by Csikszentmihalyi (1975), is a state of “opti-
mal experience” in which people report feelings of concentration and enjoyment. Flow can
be experienced in any kind of activity, but is most easily experienced when playing games,
engaging in highly skilled work, and being creative. Flow seems to occur when the task is not
so diffi cult that a participant becomes anxious, nor too easy for the participant to be bored.
Using an online survey adapted from Novak, Hoffman, & Duhachek (2003), Findlay
developed a set of Flow items using a Likert scale (strongly disagree, disagree, uncertain, agree,
13_HesseBiber_Chap13.indd 31013_HesseBiber_Chap13.indd 310 9/14/2010 9:44:02 PM9/14/2010 9:44:02 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 311
and strongly agree). Eleven propositions were presented, each associated with the dimensions
of Flow, which include a sense of clear goals, immediate feedback, the match of personal skills
to the challenge, the merger of action and awareness, a focus on the task, a feeling of being
in control, the loss of self-consciousness, the transformation of a personal sense of time so
participants lose track, and a level and a sense of fun/enjoyment. The 11 propositions were:
1. I know what I am doing
2. This is fun and enjoyable
3. I feel connected to the task.
4. I feel connected to other people
5. I am focused on what I am doing
6. I feel comfortably unaware of myself
7. The time went very quickly
8. I am in control of my own destiny
9. I am unaware of my surroundings
10. This task is worth doing anyway
11. This task is challenging but I can do it
Studies of the student groups found that most groups experience the fl ow state during a
team-meeting activity, except when the teachers continued to lecture and ask closed ques-
tions (Findlay, 2009).
Each of the previous fi ve examples highlights the versatility of the team learning system
to be employed across a wide range of research activities. In addition to generating rich data,
the highly visual “shared” view of that data allows participants to quickly and easily engage
in thematic analysis of the data. So in addition to member-checking opportunities, partici-
pants can also engage in collective sense-making. Moreover, the team learning system makes
it possible to collect text conversations (written speech acts) identifi ed by author and time
sequence that can be subjected to social network analysis in order to see whether a change
in the connectedness or relatedness of a group occurs. Findlay (2009) drew on a research
model based on complexity theory principles developed by Losada (1999), who showed
that peak team performance is highly correlated with group connectivity as measured by the
number and strength of speech acts. Disconnected groups become highly connected teams
via a phase transition (Findlay, 2009) similar to the phase transitions in physical or chemical
systems (Kauffman, 1995). Two types of social network analysis are then possible:
1. two-model analysis, which can be used to examine the pattern of concept
generation by participants in a discussion over the course of an entire learning
or decision-making activity; and
2. directed graphs analysis, to identify if and when the concepts generated by a
group spread rapidly throughout the group in such a contagious manner that
a change occurs in both the relationships between participants and the shared
knowledge of the group.
In the fi gure below, a two-mode analysis is shown with the blue ideas in the center repre-
senting the emergent knowledge of the group. The red dots represent participants in an
extended text conversation and the blue squares represent the concepts generated by one
or more participants (Figure 13.5).
13_HesseBiber_Chap13.indd 31113_HesseBiber_Chap13.indd 311 9/14/2010 9:44:02 PM9/14/2010 9:44:02 PM
312 The Handbook of Emergent Technologies in Social Research
Figure 13.5
20
6
4
Kieran
Hannah T
5
27
21
8
25
3
Hannah C
David
Dale
Natalie
Bradley
Hazel
Adam
Scott
14
26
15
19
9
17
Kerry
Vicky
Cara
22
1
10 Lily
18 11
72
Hannah D
13
Thomas
Jamie
24
Kirstie
Phil
Rebecca
Jade
Harriet
23 16
12
2
Hazel
Kerry Cara
Natalie
Thomas
Lily
Scott
Bradley
David
Adam
Hannah C
Jade
10
9
17
11 87
16
15
5
Rebecca
Hannah D Hannah T
14
12
Dale
Kieran
Harriet
Kirstie
Phil
Vicky
Jamie
13
4
3
1
Figure 13.6
13_HesseBiber_Chap13.indd 31213_HesseBiber_Chap13.indd 312 9/14/2010 9:44:02 PM9/14/2010 9:44:02 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 313
A directed graph analysis can be employed to map the fl ow of the conversations and
where they intersect. Findlay (2009) shows that closed questions result in no or mini-
mal change in the state of the group, whereas rich questions often stimulate richly con-
nected clusters of concepts that coalesce out of a conceptual “soup” of possibilities, which
becomes prototypical shared knowledge of the group. A transition occurs when concepts
generated by some of the participants appear to autocatalyze other concepts. When the
density of the interactions reaches a critical point, a large component forms (Erdos &
Renyi, 1959), which may result in a runaway reaction. Figure 13.6 below shows a directed
graph of classroom discussion where the concentration of interaction points suggests a
transition or phase shift in the knowledge-creation process.
In summary, while the team learning system supports traditional data collection activ-
ities, it also allows researchers to engage in more participatory methods both in terms
of data generation and analysis. When combined with social discourse analysis these,
methods afford researchers new ways of collaboratively generating knowledge and under-
standing the knowledge construction process. The next section will examine the relative
strengths and weaknesses of wikis and team learning systems.
Strengths and Weaknesses of Wikis and Team Learning Systems
In a sense, team learning systems and wikis are complementary tools for knowledge cre-
ation. Both allow information to be recorded and shared with others, who can then fur-
ther evolve what is written, so that it moves asymptotically toward a more perfected form.
Both make visible a large number of complex ideas.
Team learning systems support the process of crudely integrating complex streams
of ideas into higher-level concepts, models, theories, and proposals for action, whereas
wikis help multiple users perfect a description of a model of theory in all its explanatory
richness.
Timing: Wikis allow ideas to evolve by keeping a record of what was previously said,
allowing comparisons to be made between versions, but, unlike the TLS, which allows all
the participants to engage in the same activity at the same time, wikis do not permit two
users to work on the same page at the same time, although they can edit adjacent pages.
Wiki also allows previous versions to be recalled if they are considered superior to the
current version, or bring back into consciousness an element that is missing from the
latest version. A wiki has the advantage of being able to display the collective wisdom of
the group (for themselves or others) in all its informational or conceptual richness, as a
resource for all members to draw upon or to further develop. The TLS allows previous
work to be viewed and added to, but usually only to make visible previous stages of the
discourse, which may be benefi cial to later stages.
Making ideas visible: The process of knowledge creation depends to a large degree on
making as much of the data/information visible as possible for the researcher (and core-
searchers), in order to observe, detect, and extrapolate from patterns in the data.
Although wikis facilitate a kind of shared working, the participants do not have a
common real-time thinking space, and so are unable to see and build on each other’s
ideas at the same time, which limits opportunities for purposeful collective knowledge
creation.
13_HesseBiber_Chap13.indd 31313_HesseBiber_Chap13.indd 313 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
314 The Handbook of Emergent Technologies in Social Research
On the other hand, the team learning system has a common real-time space in which
multiple users contribute and see each other’s ideas simultaneously, thereby allowing
the immediate further development of the ideas, either within a current focus question
or under the guidance of a sequence of questions to some purposeful conclusion. The
TLS also helps to resolve confl icts between competing ideas by supporting the dialectical
development of overarching ideas, which helps participants develop superior explana-
tions of the phenomenon under investigation. Each person is able to contribute their
own perfected version and show it to others at the same time so the best elements of ideas
become apparent and can subsequently be incorporated into a new, more all-embracing
version. In a sense, the TLS works in the same way that a human brain works, by bring-
ing multiple streams together at the same time, so they can be compared and evolved
or resolved. Ideas are presented in “newspaper columns” for readability and alternating
colors, so that a large number of ideas can be packed into a small space and the data can
be easily reviewed.
Concept integration: An advantage of the team learning system as a tool for purpose-
ful knowledge creation is the ability to use rich question sequences to guide the collective
thinking of participants. These kinds of tools are not present in wikis. Various versions
of the team learning system, such as Researching Well (Findlay, 2007), offer processes
to support concept integration, triangulation, sense-making, and theory formation. The
team learning system also helps to resolve the muddle of competing types of thinking that
occur in “free-for-all” discussion, which is the model adopted by wikis in general.
Data collection: The team learning system allows researchers to collect data about past
or current activities. It can also be used concurrently with an experiment, both to deliver an
experimental treatment and to obtain the participants’ response to the treatment. The tool
can also be used to enlist the participants as coresearchers by inviting them to contribute
to theory formation about their own activities. The tool has the advantages of simultane-
ous concurrent input and the consolidation of all contributions into a single html or Word
document that can be immediately processed in other ways, such as copying all the ideas to
a mind-map or undertaking a concept analysis. Because all contributions are time stamped
and identifi ed by the author, the overall fl ow of a discussion can also be analyzed.
Although wikis can also be used to collect data, this is not a primary purpose, and
generally can only be achieved with considerable effort, such as embedding questions or
treatments within a page, or converting the page headings into questions.
Accessibility: Wikis are Web-based tools that are easily accessible to participants for
very low cost, between $5 and $20 per month. On the other hand, team learning systems
are generally inaccessible and require an initial investment of $US5–10,000 for a basic
portable wired USB, wireless system, or a network of computers. The tool is mostly used
in face-to-face settings and although Web-based versions are available, real-time sessions
with multiple participants require high-level facilitation skills.
Usability: Wikis are generally very intuitive to use and require little or no training for
participants. One person acts as the organizer, and invites others to join and participate
at times of their own choosing. On the other hand, the team learning system is a synchro-
nous tool and depends for its success on all participants being present for the entirety
of the session and able to coordinate their activities with each other. Good leadership or
facilitation skills are required. The team learning system makes it easy for neophyte facili-
tators to conduct complex meetings because they simply follow the question sequence. If
they need to diverge and ask supplementary questions or introduce a previously planned
13_HesseBiber_Chap13.indd 31413_HesseBiber_Chap13.indd 314 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 315
question sequence that performs a specifi c function (e.g., action plan, stakeholder analy-
sis, or feedback loop), the facilitator types in and selects a new question, or loads a new
question sequence from a repository of question sets. This kind of feature is not pres-
ent in wikis. However, researchers need to be able to give clear instructions so the group
members learn how to perform the same thinking or discourse activities at the same time.
Researchers also need to be able to craft suitable questions, which can be as diffi cult as
crafting primary and secondary research questions.
Version control: Wikis provide a tool for comparing and perfecting drafts in a side-
by-side comparison of the written word, whereas the team learning system supports the
collection and evolution of ideas. Effectively, this allows for resolving confl ict between
concepts. Because every version of contributions and changes is archived, frequent minor
changes can result, and even after a few iterations the amount of data that is collected can
become overwhelming and be diffi cult to compare and analyze.
Exploration: In conventional data collection activities, where only one person talks
at a time or data is collected via pre-prepared forms, emergent concepts are diffi cult to
explore. An advantage of the team learning system is the facility for the researcher to
observe where a conversation is going and be able to ask supplementary questions to delve
deeper into the subject. Facilitators also need to know their subject area well enough to
decide which other aspects of a conversation may be worth pursuing. This kind of feature
is not available in wikis.
Adaptability: One of the main advantages of the team learning system is the ability of
the designer/facilitator to create question sequences to perform a specifi c existing or new
research function, such as deciding/crafting the research question and sub-questions. In
some versions of the team learning system, neophyte researchers are able to learn the lan-
guage of research through a series of guided discovery workshop activities, for example:
1. Variables: Your car has stopped. Make a list of possible reasons (the variables)
why the car may have stopped.
2. Theory: A house brick has just landed on your front doorstep. What is your best
guess for why this has happened?
3. Research questions: Thinking about life, the universe, and everything, craft a
series of questions you would like to have answered.
4. Data: You have been given $50,000 to collect data about the differences between
men and women. What data must you collect, for example, height, weight, etc.?
5. Data collection: Here is an image of planet earth from space. What can you
see: location, size, shape, etc., for example, white swirls . . . (do not jump to
conclusions)?
6. Data analysis: Here are three series of numbers (a) 1,1,2,3,5,8,13,21;
(b) 1,4,9,16,25; (c) 99,92,85,78,71. What patterns can you see in these numbers?
7. Interpretation: Give your best explanation for the apparent difference between
the size of the moon at the horizon and when it is overhead.
8. Ethics: Brainstorm moral and related issues around research, for example, not
doing harm, privacy, etc.
Other research methods that have been captured in the tool include one that guides
the neophyte researcher through a series of stages in the research process: focus group
method, a triangulation method, a concept integration method, and a research project
13_HesseBiber_Chap13.indd 31513_HesseBiber_Chap13.indd 315 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
316 The Handbook of Emergent Technologies in Social Research
plan and grant application method. For example, this question sequence from Research-
ing Well captures the kind of thinking that is employed when attempting to establish
patterns in the data:
1. What evidence do we have, for example, fi ngerprint on the murder weapon, who
is present?
2. In what ways is the evidence connected, for example, fi ngerprints on the knife
are Mrs. Smith’s, does Mrs. Smith have an alibi?
3. In what ways is the evidence about some factor/aspect connected in two or more
ways, for example, how are the suspect, knife, and alibi all connected?
Developmental: As the team learning system becomes more widely adopted, new ver-
sions of the tool are being created that provide researchers with unique arrangements of
question sequences that capture specifi c learning, decision making, or research methods
(Findlay, 2009). In a sense, the tool is retroviral, having the unique ability to create new
versions in a symbiotic relationship with researchers and academics. Wikis do not have
a facility to create, save, and reuse tools that could guide a group through a thinking or
learning process. However, they could be adapted to perform this function in a rudimen-
tary way through the use of template pages, a feature found at PBworks.com.
Interoperability: Wikis and team learning systems, like many other tools used to collect,
analyze, or represent social research data, are at an early stage of development. Each of the
tools performs a discrete function, with minimal integration with other tools or ability
to transfer data from one tool to another without some kind of intermediate processing.
New versions of the team learning system are expanding its range of applications in the
social sciences by simply creating new thinking, learning, decision making, or research
questioning processes and publishing new versions of the software.
There is limited interconnection between team learning systems and wikis. Integra-
tion with data analysis tools such as social network and concept analysis software would
help to further democratize and decentralize research activities. In this scenario, research
would no longer be seen as separate from learning.
The team learning system and wikis rely on humans to make decisions about the
narrative that is created, as the human brain continues to be superior to technology in
making fi ne judgments, particularly in linguistic environments where meaning is rapidly
evolving.
Knowledge-building activities are similar to retroviral activity, which rather than
merely producing more of itself, evolves to a new form during the creation process. The
meaning of concepts and their relationship to other concepts undergo a phase transition
similar to the change in state from a solid to a liquid, liquid to a gas, or a gas to plasma.
The characteristics of the components and the rules of interacting with other components
also change.
It is our view that the role of the academic researcher is not diminished by the cre-
ation of user-centered theory/knowledge building tools, unless of course academics try to
resist the broader societal changes that are already upon us. The role of the social research
academic is to explore, discover, and invent new ways to conduct social research and to
foster that in their research students—their apprentices. However, this role may soon be
usurped by the citizen academic or citizen researcher, the knowledge industry equivalent
of the citizen journalist.
13_HesseBiber_Chap13.indd 31613_HesseBiber_Chap13.indd 316 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 317
Conclusions
Wikis and team learning systems are two emergent technologies that appear to offer much
to improving the process and product of research. Over the course of the next few decades,
we expect to see the learning-research process become more democratized, in the same
way that information and knowledge has become more routinely available and accessible
to all. Over time, we may see research head in the same direction as citizen journalism.
Citizen academics and researchers of tomorrow will no doubt directly collect their own
data and use smart tools for sense-making and theory building to create their own theo-
ries and begin applying what they learn. We can also expect to see the emergence of new
kinds of tools that help humans track whether the knowledge we create is being applied
wisely, to use the “wisdom of crowds” to know what is working and what is not. It is quite
likely that a struggle will result between experts currently responsible for the creation
and wise application of knowledge and citizen researchers in much the same way as the
artisans at the start of the Industrial Age or the secretaries and clerks at the start of the
Information Age resisted change. As new theoretical knowledge becomes more powerful
and benefi cial, it often has a dark side, if produced or used inappropriately. As a result,
the fruits of research are now scrutinized more closely than at any time in the history of
human civilization. It is no longer possible for new pharmaceuticals to be unleashed on
an unsuspecting populace without fi rst conducting extensive trials, to ensure that the new
drugs are both therapeutic and safe. It has become increasingly diffi cult in many countries
for both government and private enterprises to be established without fi rst consulting the
neighbors who will have to live with the consequences. In the same way that engineers
and builders in Western countries found during the latter half of the twentieth century
they could no longer build major projects such as infrastructure without fi rst engaging the
community affected by the project, it will become increasingly diffi cult to commercialize
the fruits of management, psychological, medical, scientifi c, and biological research, with-
out the participation of the broader community.
We anticipate that a new generation of social tools will become necessary to support
the democratization of the knowledge-creation process. It is often only when a new tech-
nology is used that we understand how it could develop in the future and what improve-
ments would make the technology more useful and powerful. Our analysis of the use of
wikis and team learning systems for the research process suggests that tools are required to
support the process of knowledge integration and formation rather than just data collec-
tion and analysis. The knowledge-creation process has reached the stage where the most
powerful new learning can only take place when we emphasize synthesis between people
rather than objective analysis and truth alone. Wikis and the team learning system are
examples of social research tools that can help us achieve this goal.
References
Benkler, Y. (2006). The wealth of networks: How social production transforms markets and freedom.
New Haven, CT: Yale University Press.
Brostrom, S. (1999). Drama games with 6-year-old children: Possibilities and limitations. In
Engestrom, Y., Miettinen, R., & Punamaki, R-L. (Eds.), Perspectives on activity theory
(pp. 250–263). Cambridge, MA: Cambridge University Press.
13_HesseBiber_Chap13.indd 31713_HesseBiber_Chap13.indd 317 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
318 The Handbook of Emergent Technologies in Social Research
Bruns, A. (2008). Blogs, wikipedia, second life and beyond: From production to produsage. New York:
Peter Lang.
Bruns, A., & Bahnisch, M. (2009). Social media: Tools for user-generated content: social drivers
behind growing consumer participation in user-led content generation [Volume 1: state of the
art]. http://eprints.qut.edu.au/21206/1/Social_Media_-_State_of_the_Art_-_March_2009.
pdf
Caldwell, B. (2006). Re-imagining educational leadership. Camberwell: ACER Press; London: Sage.
Caldwell, B., Bhowon, R., Daby, S. C., & Harris, J. (2009). Mauritius on the move: Re-imagining
school leadership, iNet (International Networking for Educational Transformation). http://
www.ssat-inet.net/pdf_secure/Mauritius%20on%20the%20move.pdf
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass.
Delbecq A. L., & van de Ven, A. H. (1971). A group process model for problem identifi cation and
program planning. Applied Behavioural Science, 7, 466–491.
Ellyard, P. (1995). Education 2001: A preferred future for Victorian state education. Melbourne:
Victorian State Secondary Principals Association.
Erdos, P., & Renyi, A. (1959). On random graphs. Publicationes Mathematicae, 6, 290–297.
Findlay, J., Fitzgerald, R., & Hobby, R. (2004). Learners as customers. Proceedings of the
International Conference on Educational Technology (ICET), Singapore.
Findlay, J., & Newman, L. (2005). Exploring ethical issues via ethical dialectical discourse using a
face-to-face team learning system, Eighth Annual Ethics & Technology Conference at St. Louis
University, June 24–24.
Findlay, J., & Fitzgerald, R. (2006). Rich design: Engaging students as capable designers and co-
creators in auto-catalytic learning contexts. Proceedings of World Conference on Educational
Multimedia, Hypermedia and Telecommunications.
Findlay, J. (2007). Researching well (Version 3.6). [Computer software]. Sydney: Zing Technologies.
Findlay, J. (2009). Learning as a game. Exploring cultural differences between teachers and learners
using a team learning system. Unpublished doctoral dissertation, University of Wollongong,
Australia.
Fitzgerald, R., & Findlay, J. (2004). A computer-based research tool for rapid knowledge-
creation. Proceeding of World Conference on Educational Multimedia, Hypermedia and
Telecommunications.
Fitzgerald, R. (2007). Open source learning: Wikis as an exemplary model of collaboration and
knowledge creation. In St. Amant, K., & Still, B. (Eds.), Handbook of research on open source
software: Technological, economic and social perspectives (pp. 681–689). Texas Tech University.
PA: IGI Global.
Hasan, H., & Crawford, K. (2006). Innovative socio-technical systems for complex decision-making.
Paper presented at the international conference on creativity and innovation in decision
making and decision support (CIDMDS), London.
Hasan, H., Meloche, J., Pfaff, C., & Willis, D. (2007). Beyond ubiquity: Co-creating corporate
knowledge with a wiki. Paper presented at mobile ubiquitous computing, systems, services and
technologies, Papeete, French Polynesia (Tahiti).
Jenkins, H. (2006). Convergence culture: Where old and new media collide. New York: NYU Press.
Kauffman, S. (1995). At home in the universe: The search for laws of self-organisation and complexity.
London: Penguin.
Keen, A. (2007). The cult of the amateur: How the democratization of the digital world is assaulting
our economy, our culture, and our values. New York: Doubleday.
Leadbeater, C. (2008). We-think: Mass innovation, not mass production: The power of mass
creativity. http://www.wethinkthebook.net.
Lee, M., & Crawford, K. (2002). Collective activity to change: A case of expansive learning. Paper
presented at the fi fth congress of the International Society for Cultural Research and Activity
Theory. Amsterdam.
13_HesseBiber_Chap13.indd 31813_HesseBiber_Chap13.indd 318 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
Collaborative Research Tools: Using Wikis and Team Learning Systems 319
LeLoup, J., & Ponerio, R. (2006). Wikipedia: A multilingual treasure trove. Language Learning &
Technology, 10(2), 12–16. http://llt.msu.edu/vol10num2/net/.
Lih, A. (2004). Wikipedia as participatory journalism: Reliable sources? Metrics for evaluating
collaborative media as a news resource. Paper presented at the 5th international symposium on
online journalism. http://jmsc.hku.hk/faculty/alih/publications/utaustin-2004-wikipedia-rc2.pdf
Losada, M. (1999). The complex dynamics of high performance teams. Mathematical and
Computer Modelling, 30, 179–192.
Mayfi eld, R. (2006). Power law of participation. http://ross.typepad.com/blog/2006/04/
power_law_of_pa.html.
Meloche, J., & Hasan, H. (2008). ICT devices as ubiquitous tools for information seeking activity.
Paper presented at The Second International Conference on Mobile Ubiquitous Computing,
Systems, Services and Technologies. UBICOMM 2008. Spain: Valencia.
Moyle, K., & Fitzgerald, R. (2008). Electronic focus groups. In Hansson, T. (Ed.), Handbook of
digital information technologies: Innovations and ethical issues (pp. 340–352). Pennysylvania:
IGI Global.
Naisbitt, J. (1982). Megatrends. New York: Warner Books.
Newman, L., & Pollnitz, L. (2002). Ethics in action. Introducing the ethical response cycle. Canberra:
Australian Early Childhood Association.
Newman, L., & Findlay, J. (2008). Communities of ethical practice: Using new technologies for
ethical dialectical discourse. Journal of Educational Technology & Society, 11(4), 16–28.
Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The infl uence of goal-directed and
experiential activities on online fl ow experiences. Journal of Consumer Psychology, 13(1–2),
3–16.
O’Reilly, T. (2004). The architecture of participation. http://www.oreillynet.com/pub/a/oreilly/tim/
articles/architecture_of_participation.htmPalmer.
Palmer, P. J. (1998). The courage to teach: Exploring the inner landscape of a teacher’s life. San
Francisco: Jossey-Bass.
Phillips, A. (2009). Case studies: Wimbledon park primary school. Wimbledon http://www.
viewsandvoices.co.uk/.
Rittel, H., & Webber, M. (1973). Dilemmas in a general theory of planning. Policy Sciences,
4, 155–169.
Shariq, S. (1999). How does knowledge transform as it is transferred? Speculations on the possibility
of a cognitive theory of knowledgescapes. Journal of Knowledge Management, 3(4), 243–251.
Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how
collective wisdom shapes business, economies, societies and nations. New York: Double Day.
Vygotsky, L. (1978). Mind in society. Cambridge, MA: Harvard University Press.
Wagner, C., Cheung, K., & Ip, R. (2006). Building semantic webs for e-government with wiki
technology. Electronic Government, 3, 36–55.
Ward, S., & Hawkins, L. (2003). Have portable GSS will travel: Focus groups at professional
conferences. In Whymark, G. (Ed.), Transformational tools for 21st century minds: TT21C2003
(pp. 60–65). Eveleigh: Knowledge Creation Press.
Waters, N., & Callan, J. (2003). A team approach sets the stage to enhance learning outcomes in
classrooms. In Whymark, G. (Ed.), Transformational tools for 21st century minds: TT21C2003
(pp. 60–65). Eveleigh: Knowledge Creation Press.
Wenger, E., McDermott, R., & Snyder, W. (2002). Cultivating communities of practice: A guide to
managing knowledge. Cambridge, MA: Harvard Business School Press.
Whymark, G., Callan, J., & Purnell, K. (2004). Online learning predicates teamwork: Collaboration
underscores student engagement. Studies in learning, evaluation, innovation and development,
1(2), http://sleid.cqu.edu.au/viewarticle.php?id = 40.
Willcox, J., & Zuber-Skerritt, O. (2003). Using the Zing team learning system (TLS) as an
electronic method for the nominal group technique (NGT). ALAR Journal, 8(1), 61–75.
13_HesseBiber_Chap13.indd 31913_HesseBiber_Chap13.indd 319 9/14/2010 9:44:03 PM9/14/2010 9:44:03 PM
